摘要
共性知识挖掘是网络舆情中实现领域可移植的有效途径,提出从共性情感元素、共性语言模式两方面建立共性舆情知识库。共性情感元素挖掘主要通过半自动方法识别并从训练库中学习量化权值实现动态扩展知识库;共性语言模式挖掘主要从语法、语义角度弥补句法分析引入的错误,提出三类修正模型,包括主语转移模型、极端情感动词模型与情感修饰短距离依赖模型。最后从宗教、酒店两个领域进行验证,证实共性知识挖掘在系统可移植性方面具有一定效果。
The common knowledge mining is an effective way for the Internet public opinion analysis. This paper builds the common knowledge base for the common sentimental elements and the common language patterns. The common sentimental knowledge is mined by the semi - supervised method from the training corpus. This knowledge base is also quantified and dynamically expanded. The common language pattern knowledge includes three kinds of fixed models, such as transform model, extreme sentimental verb model and distance dependency model. Finally the common knowledge bases are testified in the domains of religions and hotels, and proved the effectiveness in the system implant performance.
出处
《现代图书情报技术》
CSSCI
北大核心
2013年第10期59-65,共7页
New Technology of Library and Information Service
基金
教育部人文社会科学基金项目"基于多层次情感分析的网络文本舆情监测方法研究"(项目编号:10YJC870003)
北京市哲学社会科学规划基金项目"北京市公共危机事件在网络传播中的演化机制与模型研究"(项目编号:13SHC031)
国家自然科学基金项目"面向维基百科的多粒度一体化信息抽取方法研究"(项目编号:61103112)的研究成果之一
关键词
舆情分析
共性知识挖掘
情感元素
语言结构
Public opinion analysis Common knowledge mining Sentimental element Language structure
